EnergyVerse

‘ A digital energy tutor ’

Problem Statement

<aside> 🚨 In 2017, Toronto city council formed TransformTO plan, a climate advisory group to insist new strategies for reducing greenhouse gas emissions (GHG) to net zero by 2040 [1]. ****In addition, Federal government had committed $210 million dollars as Heat Pump Affordability Grant to ensure a smooth transition from natural gas furnaces to heat pumps in 2022 [2]. **** Despite the above efforts, the low-income residents of North Scarborough lack knowledge on possible energy saving measures, and reduction in cost, emission associated with the savings. Therefore, new strategies are required to change the behavior of the residents to adapt to energy optimization and greener energy lifestyle.

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Our Solution: WE CAN SAVE

Wise Energy - a Call to Act Now through Social Acceptance, Viability, and Environmental Sustainability

<aside> ✅ The solution is a step-by-step deployment of an Energy Tutor App. In first two stages of the deployment of the App, users will be educated with their previous consumption statistics and the app will suggest measures to decrease their energy usage and costs. In the second phase, the App will try to influence the user's mindset to invest towards renewable retrofits and potential long-term savings. In the third phase, the App will act as an e-commerce marketplace to connect Air source Heat Pump manufactures and the users. The app will be targeting to change the behavior of the residents by providing the split-ups about their energy consumption and projecting their future cost if they continue the current energy usage pattern. It will also suggest alternative measures to reduce the energy costs and its associated emission. The App changes the very basis of the system i.e., people's mindset and remaining changes could be achieved through the existing policies.

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Practical Humility Clause

<aside> ❓ Limitations

Accessing the end-user consumption data from Toronto Hydro and Enbridge is not possible. A group of North Scarborough residents could volunteer to donate their consumption data.
People's acceptance percentage is very uncertain. We plan to tackle it through series of camping, initial monetary promotions, social media sharing and digital marketing like YouTube videos, Instagram reels. In addition, fun quizzes in apps with financial rewards to make learning more cheerful.
The energy consumption and GHG emission shouldn’t be reduced at the cost of residents’ energy security and safety.
Aspect of app acting as an e-commerce marketplace is a very high-level assumption. For which pitching has to be done with the ASHP manufacturers and get their investments in developing a more reliable application.

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Further Explanation

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To further explain and understand our proposed solution we have identified three key areas we would like to elaborate on, this includes:

Why our solution matters
Design Criteria for our Problem
Application features
Feasibility and Viability

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Bibliography

TransformTO. (2021, Nov 19). TransformTO: Critical Steps for Net Zero by 2040. (https://www.toronto.ca/services-payments/water-environment/environmentally-friendly-city-initiatives/transformto/
Natural Resources Canada. (2022). 2021-2022 Departmental Results Report. Ministry of Natural Resources.https://natural-resources.canada.ca/transparency/reporting-and-accountability/plans-and-performance-reports/departmental-results-reports/2021-22-departmental-results-report/24708
Demirezen, G & Fung, S. A. (2021). Feasibility of Cloud Based Smart Dual Fuel Switching System (SDFSS) of Hybrid Residential Space Heating Systems for Simultaneous Reduction of Energy Cost and Greenhouse Gas Emission. Energy and Buildings, 250, https://www.sciencedirect.com/science/article/abs/pii/S0378778821005211
City of Toronto (2019). Scarborough City of Toronto Community Council Area Profiles. Toronto. Toronto City planning. https://www.toronto.ca/wp-content/uploads/2019/01/8f7c-City_Planning_2016_Census_Profile_2018_CCA_Scarborough.pdf
Programiz. (n.d). Greedy Algorithm. https://www.programiz.com/dsa/greedy-algorithm#:~:text=A greedy algorithm is an,in a top-down approach.
Stapleton, J., (2019). Scarborough Profile: Understanding and explaining poverty in Scarborough & Northern Scarborough (East Steeles Nexus). Open Policy. https://openpolicyontario.s3.amazonaws.com/uploads/2019/01/Scarborough-profile-2019.pdf
Ali Forootani, Mohammad Rastegar, Ashkan Sami, Short-term individual residential load forecasting using an enhanced machine learning-based approach based on a feature engineering framework: A comparative study with deep learning methods, https://www.sciencedirect.com/science/article/abs/pii/S0378779622003431
Demirezen, G., Fung., Deprez, M., Development and optimization of artificial neural network algorithms for the prediction of building specific local temperature for HVAC control, ****https://onlinelibrary.wiley.com/doi/abs/10.1002/er.5537

Appendix

<aside> ℹ️ You are welcome to put additional information in an appendix!

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Example Appendix Page

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This notice should be deleted from your submitted Proposed Solution Portfolio, because that will contain all of your work, with all the original template instructions being removed!

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